School of Artificial Intelligence, Hebei University of Technology, Tianjin, 300130, China.
School of Artificial Intelligence, Hebei University of Technology, Tianjin, 300130, China.
ISA Trans. 2023 Jul;138:197-211. doi: 10.1016/j.isatra.2023.03.017. Epub 2023 Mar 15.
This paper explores the design of a positive l-gain asynchronous non-fragile fault detection filter (FDF) for discrete-time positive Markov jump systems (PMJSs) based on the dynamic event-triggered method (DETM). Due to the effect of positivity on event-triggered mechanisms and non-triviality on stability of discrete-time PMJSs, a new more powerful and generic DETM that can avoid non-triviality is developed. The asynchronous situation between the non-fragile FDF modes and the system modes is effectively managed by employing a hidden Markov model. Then, the solvability criteria for issues of concern are presented by building the copositive Lyapunov function (CLF) with internal dynamic variables (IDV). An alternative sufficient condition is derived based on the obtained results. Subsequently, a co-design project of the expected dynamic event-triggered positive l-gain asynchronous non-fragile fault detection filter (DETPGAN-FFDF) and the designed DETM is proposed in this paper. Finally, the effectiveness and superiority of the approach are verified by numerical arithmetic examples and practical applications based on pest management.
本文基于动态事件触发方法（DETM），研究了离散时间正马尔可夫跳变系统（PMJS）的正增益异步非脆弱故障检测滤波器（FDF）的设计。由于正系统对事件触发机制的影响以及离散时间 PMJS 稳定性的非平凡性，开发了一种新的更强大且通用的 DETM，可以避免非平凡性。通过使用隐马尔可夫模型，有效地管理非脆弱 FDF 模式和系统模式之间的异步情况。然后，通过构建具有内部动态变量（IDV）的 copositive Lyapunov 函数（CLF），提出了关注问题的可解性准则。基于所得结果，推导出了一个替代的充分条件。随后，本文提出了预期动态事件触发正增益异步非脆弱故障检测滤波器（DETPGAN-FFDF）和设计的 DETM 的协同设计方案。最后，通过基于害虫管理的数值算例和实际应用验证了该方法的有效性和优越性。
